4.6 Article

Genetic Basis for Resistance Against Viral Nervous Necrosis: GWAS and Potential of Genomic Prediction Explored in Farmed European Sea Bass (Dicentrarchus labrax)

Journal

FRONTIERS IN GENETICS
Volume 13, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fgene.2022.804584

Keywords

nervous necrosis virus; viral nervous necrosis; VNN; single nucleotide polymorphisms; genomic prediction; quantitative trait loci; genome-wide association analysis; heritability

Funding

  1. framework of the 3rd Joint Transnational Call of the ERA-Net COFASP (Cooperation in Fisheries, Aquaculture and Seafood Processing) [6153]
  2. ERA-NET Marine Biotechnology [6153]

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Viral nervous necrosis (VNN) is an infectious disease caused by the red-spotted grouper nervous necrosis virus (RGNNV) in European sea bass. A genome-wide association analysis revealed a strong signal of quantitative trait loci (QTL) at LG12, which explained around 33% of the genetic variance. The genes HSPA4L and/or REEP1 were found to be highly relevant in managing disease-associated symptoms.
Viral nervous necrosis (VNN) is an infectious disease caused by the red-spotted grouper nervous necrosis virus (RGNNV) in European sea bass and is considered a serious concern for the aquaculture industry with fry and juveniles being highly susceptible. To understand the genetic basis for resistance against VNN, a survival phenotype through the challenge test against the RGNNV was recorded in populations from multiple year classes (YC2016 and YC2017). A total of 4,851 individuals from 181 families were tested, and a subset (n similar to 1,535) belonging to 122 families was genotyped using a similar to 57K Affymetrix Axiom array. The survival against the RGNNV showed low to moderate heritability with observed scale estimates of 0.18 and 0.25 obtained using pedigree vs. genomic information, respectively. The genome-wide association analysis showed a strong signal of quantitative trait loci (QTL) at LG12 which explained similar to 33% of the genetic variance. The QTL region contained multiple genes (ITPK1, PLK4, HSPA4L, REEP1, CHMP2, MRPL35, and SCUBE) with HSPA4L and/or REEP1 genes being highly relevant with a likely effect on host response in managing disease-associated symptoms. The results on the accuracy of predicting breeding values presented 20-43% advantage in accuracy using genomic over pedigree-based information which varied across model types and applied validation schemes.

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